{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "## 6.4高斯过程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "先回顾高斯分布相关知识，高斯分布，又叫正态分布，是连续变量经常使用的一个分布模型，一维的高斯分布如下：\n",
    "\n",
    "$$\n",
    "\\mathcal{N}\\left(x\\left|~\\mu,\\sigma^2\\right.\\right) = \\frac{1}{(2\\pi\\sigma^2)^{1/2}} \\exp\\left\\{-\\frac{1}{2\\sigma^2}(x-\\mu)^2\\right\\}\n",
    "$$\n",
    "\n",
    "其中 $\\mu$ 是均值，$\\sigma$ 是方差。\n",
    "\n",
    "$D$-维的高斯分布如下：\n",
    "\n",
    "$$\n",
    "\\mathcal{N}\\left(\\mathbf x\\left|~\\mathbf{\\mu, \\Sigma}\\right.\\right) = \\frac{1}{(2\\pi)^{D/2}} \\frac{1}{|\\mathbf\\Sigma|^{1/2}} \\exp \\left\\{-\\frac{1}{2}(\\mathbf x - \\mathbf \\mu)^\\top\\mathbf\\Sigma^{-1}(\\mathbf x - \\mathbf \\mu)\\right\\}\n",
    "$$\n",
    "\n",
    "其中，$D$ 维向量 $\\mathbf \\mu$ 是均值，$D\\times D$ 矩阵 $\\mathbf\\Sigma$ 是方差，$|\\mathbf\\Sigma|$ 是其行列式。\n",
    "\n",
    "之前我们已经看到，在均值和方差固定时，高斯函数是熵最大的连续分布，因此高斯分布的应用十分广泛。\n",
    "\n",
    "而中心极限定理告诉我们，对于某个分布一组样本 $x_1, \\dots, x_N$，他们的均值 $(x_1+\\dots+x_N)/N$ 的分布会随着 $N$ 的增大而越来越接近一个高斯分布。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "高斯过程就是就是一系列关于连续域（时间或空间）的随机变量的联合(服从多元高斯分布)，而且针对每一个时间或是空间点上的随机变量都是服从高斯分布(但其参数与时间或空间有关)的。[帮助理解高斯过程](https://www.cnblogs.com/hxsyl/p/5229746.html)\n",
    "\n",
    "+ 一个高斯过程可以被均值和协方差共同唯一决定，均值描述了样本出现的整体位置，一般设置为0，但可也可以设置为线性函数。\n",
    "\n",
    "+ 协方差反映了输入数据点之间的相似性度量，引入核函数来计算相似性。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "假定一个没有噪声的高斯回归\n",
    "+ 目标是对$f:\\mathbb{R}\\rightarrow \\mathbb R$建模\n",
    "+ $x=[x_1,...,x_N]^T,y=[y_1,...y_N]^T$\n",
    "+ 预测f在某些未知输入$x*$上的值\n",
    "\n",
    "$$\\begin{pmatrix}\n",
    "y_0\\\\\n",
    "y_1\n",
    "\\end{pmatrix}\\sim \\mathcal N\\bigg(\\begin{pmatrix}\n",
    "0\\\\\n",
    "0\n",
    "\\end{pmatrix}，\\begin{pmatrix}\n",
    "1& 0\\\\\n",
    "0& 1\n",
    "\\end{pmatrix}\\bigg) $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"ee57271e-084f-4f40-915c-12eb9676e800\">Loading BokehJS ...</span>\n",
       "    </div>"
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     "data": {
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       "\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (root.Bokeh !== undefined) {\n",
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       "    console.info(\"Bokeh: all callbacks have finished\");\n",
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       "\n",
       "  function load_libs(js_urls, callback) {\n",
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       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
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       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"ee57271e-084f-4f40-915c-12eb9676e800\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'ee57271e-084f-4f40-915c-12eb9676e800' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.7.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"ee57271e-084f-4f40-915c-12eb9676e800\").textContent = \"BokehJS is loading...\";\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.7.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.7.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.7.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
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       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"ee57271e-084f-4f40-915c-12eb9676e800\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from bokeh.plotting import figure, show\n",
    "from bokeh.io import output_notebook\n",
    "from bokeh.models import LinearColorMapper, BasicTicker, ColorBar\n",
    "from bokeh.palettes import Category10\n",
    "output_notebook()\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如下图，每次从分布中抽取10个点，依次次赋予$X\\in [0,1]$中的10个点(空间点或时间点),重复10次就得到了下图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_unit_gaussian_samples(D):\n",
    "    p = figure(plot_width=800, plot_height=500, title='Samples from a unit {}D Gaussian'.format(D))\n",
    "\n",
    "    xs = np.linspace(0, 1, D)\n",
    "    for color in Category10[10]:\n",
    "        ys = np.random.multivariate_normal(np.arange(D), np.eye(D))\n",
    "        p.line(xs, ys, line_width=1, color=color)\n",
    "    return p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "      root._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
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       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
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       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
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       "        delete root._bokeh_onload_callbacks\n",
       "      }\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      root._bokeh_onload_callbacks.push(callback);\n",
       "      if (root._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      root._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          root._bokeh_is_loading--;\n",
       "          if (root._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"4c94f5cc-7b8f-437b-a2f8-edabc41e1671\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '4c94f5cc-7b8f-437b-a2f8-edabc41e1671' but no matching script tag was found. \")\n",
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       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
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     "metadata": {},
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   "source": [
    "show(plot_unit_gaussian_samples(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 6.4.1 重新考虑线性回归"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "考虑⼀个模型M，它被定义为由向量ϕ(x)的元素给出的M个固定基函数的线性组合，即$$y(x)=w^T\\phi(x)$$\n",
    "考虑w上的一个先验分布:$$p(w)=\\mathcal N(w|0,\\alpha ^{-1}I)$$其中$\\alpha$为超参数，代表精度。记函数值的集合记作向量$\\mathbf{y}$,$\\mathbf y=\\Phi w$\n",
    "\n",
    "y是由w的元素给出的服从⾼斯分布的变量的线性组合，因此它本⾝是服从⾼斯分布,其均值为0方差为$$cov[\\mathbf y]=\\mathbb E[\\mathbf{yy^T}]=\\Phi\\mathbb E[ww^T]\\Phi^T=\\frac{1}{\\alpha}\\Phi\\Phi^T=K$$\n",
    "⾼斯过程的确定通过给定两个x处的函数值y(x)的协⽅差来完成。这个协⽅差由核函数确定:\n",
    "$$\\mathbb E[y(x_n)y(x_m)]=k(x_n,x_m)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.4.2 用于回归的高斯过程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "已知的输入向量$x=[x_1,...x_N]$,预测$x_{N+1}$处的$t_{N+1}$\n",
    "$$t_n=y_n+\\epsilon_n$$\n",
    "$$p(t_n|y_n)=\\mathcal N(t_n|y_n,\\beta^{-1})$$\n",
    "目标值$t=(t_1,...,t_N)^T$的联合概率分布时一个各向同性的高斯分布\n",
    "$$p(t|y)=\\mathcal N(t|y,\\beta^{-1}I_N)$$\n",
    "边缘概率分布$$p(y)=\\mathcal N(y|0,K)$$\n",
    "为了找到一输入值$x_1,...,x_N$为条件的边缘概率分布$p(t)$需要对y积分：$$p(t)=\\int{p(t|y)p(y)dy}=\\mathcal N(t|0,C)$$\n",
    "\n",
    "已知：\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "p(\\mathbf x)&=\\mathcal N(\\mathbf x~|~\\mathbf \\mu, \\mathbf \\Lambda^{-1}) \\\\\n",
    "p(\\mathbf y|\\mathbf x)&=\\mathcal N(\\mathbf y~|~\\mathbf{Ax+b}, \\mathbf L^{-1}) \\\\\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "我们有\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "p(\\mathbf y)&=\\mathcal N(\\mathbf y~|~\\mathbf{A\\mu+b}, \\mathbf L^{-1}+\\mathbf A\\mathbf \\Lambda^{-1}\\mathbf A^\\top) \\\\\n",
    "p(\\mathbf x|\\mathbf y)&=\\mathcal N(\\mathbf y~|~\\mathbf \\Sigma\\left\\{ \\mathbf A^\\top \\mathbf{L(y-b)} + \\mathbf{\\Lambda\\mu} \\right\\}, \\mathbf \\Sigma) \\\\\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "其中 $\\mathbf \\Sigma = (\\mathbf\\Lambda + \\mathbf A^\\top\\mathbf L\\mathbf A)^{-1}$。\n",
    "\n",
    "协方差矩阵$$C=(x_n，x_m)=k(x_n,x_m)+\\beta^{-1}\\delta_{nm}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "接着计算预测分布$p(t_N+1|\\mathbf t_N)$,先找到联合概率分布$p(\\mathbf t_{N+1})=\\mathcal N(\\mathbf t_{N+1}|0,C_{N+1})$\n",
    "$$C_{N+1}=\\begin{pmatrix}C_N&k\\\\k^T&c\\end{pmatrix}$$\n",
    "其中$k=k(x_n,x_{N+1})$,n,m=1,...,N$,c=k(x_{N+1},x_{N+1})+beta^{-1}$\n",
    "$p(t_N+1|\\mathbf t_N)$也为高斯分布,\n",
    "均值为$$m(x_{N+1})=\\mu(x)+k^TC_N^{-1}(t-\\mu(x)$$\n",
    "方差为$$\\sigma^2(x_{N+1})=c-k^TC_N^{-1}k$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "回到例子，我们用Sqared Exponential kernel来定义来计算协方差矩阵$$k(x,x')=exp(-\\frac{(x-x')^2}{2})$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "            var render_items = [{\"docid\":\"8c7d8253-8527-47b8-915d-ba129450f053\",\"elementid\":\"78604d48-9373-4082-bf33-4812a04ab63b\",\"modelid\":\"22aa6325-b6c5-4d75-aa8e-f878421eee85\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
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       "  \n",
       "    if (root._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
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       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def k(xs,ys,sigma=1,l=1):\n",
    "    dx=np.expand_dims(xs,1)-np.expand_dims(ys,0)\n",
    "    return (sigma**2)*np.exp(-((dx)**2)/2)\n",
    "def m(x):\n",
    "    return np.zeros_like(x)\n",
    "\n",
    "N = 100\n",
    "x = np.linspace(-2, 2, N)\n",
    "y = np.linspace(-2, 2, N)\n",
    "d = k(x, y)\n",
    "\n",
    "color_mapper = LinearColorMapper(palette=\"Plasma256\", low=0, high=1)\n",
    "\n",
    "p = figure(plot_width=400, plot_height=400, x_range=(-2, 2), y_range=(-2, 2),\n",
    "           title='Visualisation of k(x, x\\')', x_axis_label='x',\n",
    "           y_axis_label='x\\'', toolbar_location=None)\n",
    "p.image(image=[d], color_mapper=color_mapper, x=-2, y=-2, dw=4, dh=4)\n",
    "\n",
    "color_bar = ColorBar(color_mapper=color_mapper, ticker=BasicTicker(),\n",
    "                     label_standoff=12, border_line_color=None, location=(0,0))\n",
    "\n",
    "p.add_layout(color_bar, 'right')\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 1],\n",
       "       [1, 1]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.expand_dims([2,2],1)-np.expand_dims([1,1],0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: RuntimeWarning: covariance is not positive-semidefinite.\n",
      "  \"\"\"\n"
     ]
    },
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       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
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       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
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       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(window));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p=figure(plot_width=800,plot_height=500)\n",
    "D=10\n",
    "xs=np.linspace(0,1,D)\n",
    "for color in Category10[10]:\n",
    "    ys=np.random.multivariate_normal(np.arange(xs.shape[0]),k(xs,xs))\n",
    "    p.circle(xs,ys,size=3,color=color)\n",
    "    p.line(xs,ys,line_width=1,color=color)\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "提高维数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:9: RuntimeWarning: covariance is not positive-semidefinite.\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"bd89a7c7-2b10-4247-baa6-ad16f2fdf522\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(root) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "  \n",
       "    var force = false;\n",
       "  \n",
       "    if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      root._bokeh_onload_callbacks = [];\n",
       "      root._bokeh_is_loading = undefined;\n",
       "    }\n",
       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      root._bokeh_timeout = Date.now() + 0;\n",
       "      root._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "  \n",
       "    function display_loaded() {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"bd89a7c7-2b10-4247-baa6-ad16f2fdf522\");\n",
       "        if (el != null) {\n",
       "          el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "        }\n",
       "      } else if (Date.now() < root._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "  \n",
       "  \n",
       "    function run_callbacks() {\n",
       "      try {\n",
       "        root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      }\n",
       "      finally {\n",
       "        delete root._bokeh_onload_callbacks\n",
       "      }\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      root._bokeh_onload_callbacks.push(callback);\n",
       "      if (root._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      root._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          root._bokeh_is_loading--;\n",
       "          if (root._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"bd89a7c7-2b10-4247-baa6-ad16f2fdf522\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'bd89a7c7-2b10-4247-baa6-ad16f2fdf522' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = 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       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i].call(root, root.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < root._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!root._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        root._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"bd89a7c7-2b10-4247-baa6-ad16f2fdf522\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (root._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(window));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 100\n",
    "xs = np.linspace(-5, 5, n)\n",
    "K = k(xs, xs)\n",
    "mu = np.arange(xs.shape[0])\n",
    "\n",
    "p = figure(plot_width=800, plot_height=500)\n",
    "\n",
    "for color in Category10[5]:\n",
    "    ys = np.random.multivariate_normal(mu, K)\n",
    "    p.line(xs, ys, line_width=2, color=color)\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 高斯过程预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "假设$0.03X^5+0.2x^4-0.1x^3-2.4x^2-2.5x+6$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"f4c6bdf7-5650-4171-9613-c691bbedb584\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(root) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "  \n",
       "    var force = false;\n",
       "  \n",
       "    if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      root._bokeh_onload_callbacks = [];\n",
       "      root._bokeh_is_loading = undefined;\n",
       "    }\n",
       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      root._bokeh_timeout = Date.now() + 0;\n",
       "      root._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "  \n",
       "    function display_loaded() {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"f4c6bdf7-5650-4171-9613-c691bbedb584\");\n",
       "        if (el != null) {\n",
       "          el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "        }\n",
       "      } else if (Date.now() < root._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "  \n",
       "  \n",
       "    function run_callbacks() {\n",
       "      try {\n",
       "        root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      }\n",
       "      finally {\n",
       "        delete root._bokeh_onload_callbacks\n",
       "      }\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      root._bokeh_onload_callbacks.push(callback);\n",
       "      if (root._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      root._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          root._bokeh_is_loading--;\n",
       "          if (root._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"f4c6bdf7-5650-4171-9613-c691bbedb584\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'f4c6bdf7-5650-4171-9613-c691bbedb584' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = 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Application\",\"version\":\"0.12.7\"}};\n",
       "            var render_items = [{\"docid\":\"5e77a216-8567-4165-b605-ed6bdbe99ca1\",\"elementid\":\"f4c6bdf7-5650-4171-9613-c691bbedb584\",\"modelid\":\"9eebe300-4a6c-43d5-8b5a-b4818780da16\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i].call(root, root.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < root._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!root._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        root._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"f4c6bdf7-5650-4171-9613-c691bbedb584\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (root._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(window));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# coefs[i] is the coefficient of x^i\n",
    "coefs = [6, -2.5, -2.4, -0.1, 0.2, 0.03]\n",
    "\n",
    "def f(x):\n",
    "    total = 0\n",
    "    for exp, coef in enumerate(coefs):\n",
    "        total += coef * (x ** exp)\n",
    "    return total\n",
    "\n",
    "xs = np.linspace(-5.0, 3.5, 100)\n",
    "ys = f(xs)\n",
    "\n",
    "p = figure(plot_width=800, plot_height=400, x_axis_label='x',\n",
    "           y_axis_label='f(x)', title='The hidden function f(x)')\n",
    "p.line(xs, ys, line_width=2)\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x_obs = np.array([-4, -1.5, 0, 1.5, 2.5, 2.7])\n",
    "y_obs = f(x_obs)\n",
    "\n",
    "x_s = np.linspace(-8, 7, 80)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#计算新的协方差矩阵\n",
    "K = k(x_obs, x_obs)\n",
    "K_s = k(x_obs, x_s)\n",
    "K_ss = k(x_s, x_s)\n",
    "\n",
    "K_sTKinv = np.matmul(K_s.T, np.linalg.pinv(K))\n",
    "\n",
    "mu_s = m(x_s) + np.matmul(K_sTKinv, y_obs - m(x_obs))\n",
    "Sigma_s = K_ss - np.matmul(K_sTKinv, K_s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "高斯过程中，每个随机变量的方差中会包含不确定性，而矩阵中第i个随机变量的协方差是Σ∗ii，也就是矩阵Σ∗的一个对角元素，所以在这里，我们得到样本的标准差为±2。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:16: RuntimeWarning: covariance is not positive-semidefinite.\n",
      "  app.launch_new_instance()\n"
     ]
    },
    {
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       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
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       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
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       "            var render_items = [{\"docid\":\"b39f9561-754b-4ef3-bb18-d81819dddfe6\",\"elementid\":\"e8d4f4ff-2141-4fd6-b9b5-b59f5a98f333\",\"modelid\":\"bca4f8ac-dc78-47eb-90cf-ad0a2778c8ec\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i].call(root, root.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < root._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!root._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        root._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"e8d4f4ff-2141-4fd6-b9b5-b59f5a98f333\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (root._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(window));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = figure(plot_width=800, plot_height=600, y_range=(-7, 8))\n",
    "\n",
    "y_true = f(x_s)\n",
    "p.line(x_s, y_true, line_width=3, color='black', alpha=0.4,\n",
    "       line_dash='dashed', legend='True f(x)')\n",
    "\n",
    "p.cross(x_obs, y_obs, size=20, legend='Training data')\n",
    "\n",
    "stds = np.sqrt(Sigma_s.diagonal())\n",
    "err_xs = np.concatenate((x_s, np.flip(x_s, 0)))\n",
    "err_ys = np.concatenate((mu_s + 2 * stds, np.flip(mu_s - 2 * stds, 0)))\n",
    "p.patch(err_xs, err_ys, alpha=0.2, line_width=0, color='grey',\n",
    "        legend='Uncertainty')\n",
    "\n",
    "for color in Category10[3]:\n",
    "    y_s = np.random.multivariate_normal(mu_s, Sigma_s)\n",
    "    p.line(x_s, y_s, line_width=1, color=color)\n",
    "\n",
    "p.line(x_s, mu_s, line_width=3, color='blue', alpha=0.4, legend='Mean')\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "回想一下Ridge回归\n",
    "$$w=\\mathop{argmin}_{w\\in\\mathbb R^d}\\lVert t-\\Phi w\\lVert^2_2+\\frac{1}{2}\\lVert\\lambda\\lVert^2$$\n",
    "令$$\\Phi\\Phi^T=k^T,C_N^{-1}=\\Phi\\Phi^T+\\frac{\\lambda^2}{2}$$\n",
    "ridge回归是一种最最最最简单的高斯过程回归，核函数就是简单的点积."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
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   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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